Python for Data Science and Machine Learning

About This Course

“Python for Data Science and Machine Learning” is a comprehensive course designed to equip learners with the necessary skills and knowledge to effectively utilize Python in the fields of data science and machine learning. This course is tailored for individuals who want to harness the power of Python to analyze data, build predictive models, and extract valuable insights.

Throughout the course, you will gain a solid understanding of the fundamental concepts and techniques used in data science and machine learning. Starting with data manipulation and exploration, you will learn how to use Python libraries such as Pandas and NumPy to clean, transform, and analyze datasets. You will also delve into data visualization using tools like Matplotlib and Seaborn to create insightful visual representations.

The course then progresses to cover machine learning algorithms and techniques. You will learn how to apply popular Python libraries such as scikit-learn and TensorFlow to train and evaluate models for classification, regression, clustering, and more. You will gain hands-on experience in feature engineering, model selection, and hyperparameter tuning to optimize model performance.

Furthermore, the course introduces you to advanced topics such as natural language processing (NLP) and deep learning. You will discover how to process and analyze text data using Python libraries like NLTK and spaCy. Additionally, you will explore deep learning frameworks like Keras and PyTorch to build and train neural networks for tasks such as image classification and natural language processing.

By the end of the course, you will be proficient in using Python for data science and machine learning tasks. You will be able to manipulate and analyze data, build and evaluate predictive models, and communicate insights effectively through data visualization. This course empowers you to leverage Python’s extensive ecosystem and popular libraries to solve real-world data challenges and unlock the potential of data-driven decision-making.

Whether you are a data analyst, aspiring data scientist, or professional seeking to enhance your skill set, “Python for Data Science and Machine Learning” provides you with a solid foundation to excel in the exciting and rapidly evolving field of data science.

 

Learning Objectives

Study of data preprocessing techniques, such as cleaning, transforming, and handling missing data.
Techniques for exploratory data analysis (EDA) to gain insights and understanding from datasets.
Exploration of supervised and unsupervised machine learning algorithms using Python's Scikit-learn library.
Practice in evaluating model performance and tuning hyperparameters for optimal results.

This course is best for:

  • "Python for Data Science and Machine Learning" is for individuals interested in utilizing Python for data analysis, machine learning, and extracting insights from data.

Curriculum

18 Lessons

Introduction to Data Science and Machine Learning with Python

Foundations of Data Science: Introduction and Principles
Python Programming for Data Analysis and Machine Learning
Exploring and Visualizing Data with Python
Machine Learning Basics: Algorithms and Concepts
Assignments

Python Basics and Data Manipulation for Data Science

Data Visualization using Python Libraries

Data Preprocessing and Cleaning with Python

Model Evaluation and Validation in Python

Course Provided By

VEDUCARE

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Enrolkart Course - 2023-07-19T030756.592
Level
Intermediate
Lectures
18 lectures
Language
English
Enrollment validity: Lifetime

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